The problem of spam in established communication technologies, such as electronic mail, is well-recognized. Spam may include unsolicited messages sent by a computer over a network to a large number of recipients. Spam includes unsolicited commercial messages, but spam has come to be understood more broadly to additionally include unsolicited messages sent to a large number of recipients, and/or to a targeted user or targeted domain, for malicious, disruptive, or abusive purposes, regardless of commercial content. For example, a spammer might send messages in bulk to a particular domain to exhaust its resources.
However, a sender of a large number of messages might not be considered a spammer. For example, an educational, financial institution, health institution, or the like, might send a large number of messages to its alumni, members, or the like. Similarly, known and/or generally acceptable merchants might send large number of messages that the recipients may actually want to receive. Such bulk message distributors may be well known by its recipients, who may actually seek to receive the messages. Thus, a sender of a large number of messages cannot be classified based solely upon the quantity of messages it sends. Because recipients of the bulk messages may know and accept messages from these senders, filters need to be tuned to allow the messages to be delivered. Difficulty often arises in algorithmically classifying a sender as a spammer, a reputable source, or somewhere in between. Therefore, it is with respect to these considerations and others that the present invention has been made.